Serum of 79 workers exposed to silica and 25 healthy controls cases were determined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). 7 protein peaks were selected and used by artificial neural network (ANN) to establish a diagnostic model. A blinded test showed that accuracy, sensitivity and specificity were 91.35%, 93.69%, and 84.52%, respectively. The diagnostic pattern was also established to distinguish each stage of silica-exposed population. The diagnostic pattern worked excellently with 89.23%, 94.20% and 92.37% of accurate rate for classifying phase 0, phase 0+, and phase I of silicosis, respectively.
Biomarkers ; blood ; Blood Proteins ; analysis ; Humans ; Neural Networks (Computer) ; Sensitivity and Specificity ; Silicosis ; blood ; classification ; diagnosis ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ; methods

OBJECTIVE To explore the construction of selection system for drug directory of the county-level medical community based on multi-criteria decision analysis， and provide decision-making basis for the selection of drug directory of medical community. METHODS Taking county-level medical community in Chongqing as an example，Delphi method and analytic hierarchy process were employed to construct the selection system for drug directory of the county-level medical community. Selected drugs were quantitatively scored based on the constructed index system， and the drug directory was selected according to the drug’s comprehensive score. The implementation effect of the directory was then evaluated through questionnaire surveys one year after the implementation of the directory. RESULTS The expert authority coefficients of the two rounds of consultation were＞ 0.8， with Kendall’s W values of 0.213 and 0.196， respectively （P＜0.001）. Finally， the selection system for drug directory of the medical community was determined to include five evaluation dimensions： safety， effectiveness， economy， accessibility， and innovation， along with eight evaluation indicators. In the drug directory selected according to the above method， the proportions of centrally procured drugs， medical insurance drugs， and essential drugs had all increased compared to before the selection； the comprehensive scores of chemical drugs ranged from 50.25 to 96.31 scores， and the proportion of drugs scoring between 70 and 100 scores had increased from 78.06% before selection to 85.82%. Among them， antiparasitic drugs had the highest comprehensive scores， while drugs for the digestive tract and metabolism were the most numerous. The evaluation scores of each indicator and the comprehensive scores of drugs in the drug directory after the selection process increased significantly than before selection （P＜ 0.05）. CONCLUSIONS The selection system for drug directory of the county-level medical community constructed in this study is scientific， objective and operable. This process facilitates the promotion of standardized and unified management of drugs in the medical community.